Triple
T28024794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DJ Durel |
E707788
|
entity |
| Predicate | notableGenreScene |
P22737
|
FINISHED |
| Object | Atlanta trap |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Atlanta trap | Statement: [DJ Durel, notableGenreScene, Atlanta trap]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableGenreScene Context triple: [DJ Durel, notableGenreScene, Atlanta trap]
-
A.
notableScene
Indicates that a particular scene is especially significant, memorable, or noteworthy within a work or context.
-
B.
associatedWithGenreScene
chosen
Indicates that an entity is connected or related to a particular genre scene, such as a specific stylistic or cultural subcommunity within a broader genre.
-
C.
notableSceneAssociation
Indicates an association between an entity and a notable or memorable scene in which it prominently appears or plays a significant role.
-
D.
subgenreScene
Indicates that one scene is a more specific subgenre or subtype of another, broader scene category.
-
E.
filmSceneType
Indicates the type or category of a scene within a film, such as its narrative function, style, or setting.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ef96baf3a881909a2b63844185dddd |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_6a007241df8081909dbad651fda82aa7 |
completed | May 10, 2026, 11:55 a.m. |
| PD | Predicate disambiguation | batch_6a0071e77ed081908cd618da8977d878 |
completed | May 10, 2026, 11:54 a.m. |
Created at: April 27, 2026, 8:12 p.m.